Liver fibrosis, driven by chronic injury, hinges on hepatic stellate cell (HSC) activation. Microfibrillar-associated protein 4 (MFAP4), an extracellular matrix protein critical for elastic fiber assembly, is upregulated in hepatic fibrosis, yet its mechanistic role remains unclear. Liver fibrosis was induced in wild-type and Mfpa4 knockout mice using CCl₄ and TAA, while LX-2 cells were activated with TGF-β1. Bioinformatics analysis, histopathology, double immunofluorescence, flow cytometry, Transwell co-culture systems, Western blot, and quantitative PCR were employed to identify the primary intrahepatic cell types expressing MFAP4 and assess its effects on HSC activation and apoptosis. MFAP4 is upregulated in cirrhotic livers and is actively expressed in HSC. Single-cell RNA sequencing analysis and Transwell co-culture experiments revealed that the pro-fibrotic effects of MFAP4 were primarily mediated through HSCs rather than hepatocytes. Inhibition of MFAP4 significantly reduces the expression of fibrosis markers in HSC, inhibits their proliferation and migration, while overexpression of MFAP4 results in the opposite effect, accompanied by enhanced apoptosis resistance. In mouse models, global knockout of Mfap4 significantly alleviates CCl₄- and TAA-induced liver fibrosis. Mechanistic analysis reveals that MFAP4 binds to integrin αvβ3 on the HSC membrane, activating the FAK/PI3K/NFκB signaling pathway, which promotes HSC activation and survival, ultimately exacerbating liver fibrosis. Moreover, MFAP4 mediates a self-sustaining feedback loop via integrin αvβ3, maintaining HSC activation and further promoting fibrosis progression. MFAP4 governs HSC activation and apoptosis resistance via integrin αvβ3-dependent FAK/PI3K/NFκB signaling. Targeting MFAP4 mitigates fibrosis by altering HSC fate.

Acute-on-chronic liver failure (ACLF) is a syndrome characterized by systemic inflammation, leading to high short-term mortality. The lymphocyte to high-density lipoprotein ratio (LHR) has been introduced as a novel marker of inflammation. However, its role as a prognostic inflammatory biomarker in the context of hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) has received limited attention. We retrospectively included 272 patients with HBV-ACLF who met the definition of APALC. Data on clinical features and laboratory tests were collected from medical records within 24 h. Logistic regression was used to identify risk factors for poor short-term prognosis, and LHR-based prediction (LHRB) models were constructed based on risk factors. Furthermore, the accuracy of the LHRB model was validated through rigorous testing. In the survival and death groups, there were statistical differences in their CTP, MELD, MELD-Na, COSSH-ACLF II scores, and LHR. Multivariate logistic regression identified seven predictors significantly associated with 28-day mortality. Furthermore, statistically significant differences in short-term mortality and certain clinical laboratory tests for poor prognosis were observed between the high and low LHR groups. To assess the predictive performance of various models in terms of short-term mortality, the area under the receiver operating characteristic curve (AUROC) was calculated. The AUROC values for the CTP, MELD, MELD-Na, COSSH-ACLF II, and LHRB models were found to be 0.725, 0.788, 0.772, 0.871, and 0.877, respectively. The results in the validation group were similar to those in the training group, and the validation results suggested excellent performance of the LHRB model. LHR levels have the potential to serve as indicators for the prognosis of HBV-ACLF. Additionally, the recently developed LHRB model offers an accessible risk assessment tool.

Acute-on-chronic liver failure (ACLF) is characterized by a systemic inflammatory response, predominantly associated with hepatitis B virus in the Asia-Pacific region, with a high short-term mortality rate. The platelet to high-density lipoprotein ratio (PHR) has been used to predict the prognosis of patients with various inflammatory diseases. We aim to is to use the PHR to predict the short-term prognosis of patients with HBV-ACLF. In this study, we retrospectively analyzed clinical data from 270 HBV-ACLF patients. Using logistic regression, we identified independent risk factors for short-term mortality and developed a prognostic model. This model was then validated, compared, and its clinical utility assessed via decision curve analysis (DCA). Among the 270 HBV-ACLF patients, 98 patients died within 28 days. The deceased group exhibited a higher proportion of severe hepatic encephalopathy and ascites. Additionally, there was a statistically significant difference (P = 0.046) in the novel inflammation scoring system, PHR, between the two groups. Following stringent variable selection, PHR was identified as a predictive factor for short-term mortality in HBV-ACLF patients using logistic regression analysis (OR: 0.835 (0.756–0.999), P = 0.009), and it exhibited a synergistic effect with certain traditional scores. The prognostic model constructed based on PHR demonstrated a superior ability to predict short-term mortality compared to traditional scores such as Child-Turcotte-Pugh (AUC: 0.889). Evaluation using calibration curves and decision curve analysis (DCA) suggested its practical utility. PHR can predict short-term mortality in patients, with a low PHR upon admission being associated with an increased risk of death.